Endoscopic optical coherence elastic image motion artifact suppression method

Abstract

The invention discloses an endoscopic optical coherence elastic image motion artifact suppression method. The method comprises the following steps: acquiring an intensity image and a phase difference image corresponding to a target OCT spectral signal; for the intensity image, correcting a morphological distortion based on a frequency of motion disturbance; for the phase difference image, detecting the moment when the excitation causes deformation in the imaging object, subtracting the displacement caused by the motion in the detected displacement, and keeping the displacement caused by the excitation to correct the deformation amount deviation; and reconstructing an optical coherence elastography image according to the form distortion correction result and the deformation quantity deviation correction result. According to the method, the elastic value deviation in the endoscopic optical coherence elastography image caused by physiological movement and the form distortion of the imaging object can be corrected at the same time, so that interference factors such as movement artifacts and the like are effectively inhibited.

Description

Technical Field

[0001] The present invention relates to the technical field of medical image processing, and more particularly to a method for suppressing motion artifacts in endoscopic optical coherence elasticity images. Background Art

[0002] Endoscopic imaging methods are important means of diagnosing cardiovascular diseases. Intravascular ultrasound (IVUS) technology and intravascular OCT (IVOCT) technology have been widely used in clinical practice. They can observe the morphology and thickness of intravascular plaques and assess the vulnerability of plaques from a morphological perspective, which has greatly promoted the identification of vulnerable plaques in atherosclerosis. However, in the pathological process of atherosclerosis, the elasticity of vascular wall tissue will undergo significant changes, such as fibrosis and calcification, and these changes often occur before visible morphological changes. Therefore, evaluating the elastic properties of the vascular wall is more helpful for the early diagnosis of vulnerable plaques. However, the existing IVUS and IVOCT technologies used to evaluate vascular morphological information are unable to obtain elastic information of biological tissues.

[0003] Optical coherence elastography (OCE), an extension of phase-sensitive optical coherence tomography (PS-OCT), is an emerging elasticity imaging technique that utilizes the phase information of interfering light for imaging. It boasts high resolution, high displacement detection sensitivity, and high accuracy. The principle of OCE is to apply pressure to biological tissue through external excitation methods, such as ultrasound, mechanical stimulation, air pulses, or laser pulses, to induce deformation. PS-OCT is then used to measure the deformation and finally calculate elasticity. The main methods for calculating elasticity are compression and transient methods. With compression, under the same pressure, the sample deformation varies depending on the Young's modulus: a smaller deformation indicates a larger Young's modulus, and thus a stiffer sample. With transient methods, the transverse propagation velocity of the deformation (shear wave velocity) is measured; a higher velocity corresponds to a higher Young's modulus. Among various excitation methods, ultrasonic excitation generates acoustic radiation force, providing the excitation pressure. This advantage facilitates control of both force and velocity, making it a popular choice. Therefore, OCE technology, which combines precise ultrasound excitation with highly sensitive displacement detection using PS-OCT, can accurately quantify the elastic properties of biological tissues based on morphological information, making it a valuable tool for elasticity assessment. OCE technology has been clinically applied in ophthalmology and dermatology, demonstrating its potential to facilitate early and accurate diagnosis.

[0004] Endoscopic optical coherence imaging (OCE) technology is urgently needed for early diagnosis of vulnerable plaques, but currently no clinically available products exist. One major reason for this is that endoscopic OCE imaging is susceptible to physiological patient motion, including respiration, cardiac / arterial pulsation, and intestinal peristalsis. This can easily lead to motion artifacts, resulting in not only morphological distortions in the image but also deviations in elastic deformation. Motion artifacts are caused by slow imaging speeds. These slow imaging speeds are due to two reasons: First, OCE requires M-mode scanning. This scanning method applies excitation and probes at the same location for a period of time to record the deformation of the target tissue, which is recorded as one M-mode image. The M-mode imaging process is then repeated at the next location. M-mode scanning slows the overall imaging speed of the OCE system and makes the imaging process susceptible to motion artifacts. This is primarily manifested in vertical misalignment between each line scan (A-scan), resulting in distortion of the target object in the cross-sectional scan (B-scan) image, or vertical misalignment between each B-scan image, resulting in distortion of the target object in the 3D volume image (or longitudinal section image). Figure 1 Normal and motion-affected OCT 3D volume images are shown. Figure 1 (a) is a normal OCT three-dimensional image. Figure 1 (b) is an OCT three-dimensional image affected by motion artifacts. The imaging object is the retina, x is the fast axis scanning direction, y is the slow axis scanning direction, and z is the depth direction. Figure 1 (b) shows significant morphological distortion in the y-direction. Second, the application of excitation requires a sustained period of time, and the process of excitation is subject to disturbances caused by motion. After excitation, the tissue deforms, and the process of reaching maximum deformation is affected by motion. M-mode imaging is used to record this deformation process. Figure 2 is a deformation diagram, where Figure 2 (a) is a schematic diagram of a normal deformation process. Figure 2 (b) is a schematic diagram of the deformation process affected by motion and indicates the offset of the displacement. Figure 2 (c) is the normal OCE image, Figure 2 (d) is an OCE image affected by motion. The vertical stripes indicated by the arrows are deformation deviations. According to the Doppler principle, the speed of deformation is proportional to the phase difference detected by PS-OCT. Figure 2 The dashed line in (a) is the velocity curve, which is the process of tissue deformation velocity change detected by PS-OCT. Figure 2The solid line in (a) is the displacement curve, and the dashed line is the time integral of the deformation magnitude, representing the process of change in deformation magnitude. The deformation magnitude, which reflects the elastic properties of the tissue, is the maximum value of the deformation curve. Because PS-OCT detects not only the velocity of deformation caused by excitation but also the velocity caused by motion, the velocity curve is offset, and thus the displacement curve as well. This results in a biased measured deformation magnitude and an inability to accurately reflect the elastic properties of the tissue.

[0005] Currently, there is no method to correct the morphological distortion in endoscopic OCT images. In ocular OCT examination technology, there is a method that uses spatial polynomial fitting to identify feature layers to correct the morphological distortion of OCT images. Figure 3 As shown, the method includes: obtaining an eye OCT slow axis scan image ( Figure 3 (a)), the imaging object is the retina; by identifying the characteristic layer, the upper surface of the characteristic layer is marked in the image ( Figure 3 (b) green line); perform curve fitting, smooth the boundary curve of the feature layer, and use polynomial fitting to obtain the fitting curve ( Figure 3 (c)); perform image correction according to the fitting curve, and make the image affected by motion close to the fitting curve, so as to obtain the corrected image ( Figure 3 (d)). In this method, the inner segment / outer segment (IS / OS) layer of the retina is selected as the feature layer because this layer remains unchanged in most types of lesions and its boundary line is close to a quadratic function curve, making its features easier to identify and fit.

[0006] In addition, there is currently no method to correct for deformation deviations in endoscopic OCE scenes. In ocular OCE inspection technology, there is a method for calculating the time difference image of the Doppler phase difference image to suppress eye motion artifacts. This method is used in the transient elasticity calculation method to improve the accuracy of elasticity calculation, see Figure 4 shown. Figure 4 (a) is a schematic diagram showing the relationship between the Doppler phase difference M-mode scanning image and the cross-sectional image. Figure 4 (b) is a method for calculating the time difference image of the Doppler phase difference image. Artifact suppression methods such as Figure 4 As shown in (b), the imaging object is the cornea. Each small image in the first row is a cross-sectional display of the Doppler phase difference image, and the time interval between each small image is 0.2ms. The second to fifth rows are the time difference images ΔI0(t) of the Doppler phase difference image at different delay time intervals T. The calculation method is:

[0007] ΔI0(t)=I0(t)-I0(t+T)

[0008] Where I0(t) is the Doppler phase difference image, t is time, and T is the delay interval. Assuming the eye remains motionless during the appropriate time interval T, this differential method can avoid the influence of eye movement and obtain a Doppler phase difference image with a high signal-to-noise ratio, thereby ensuring the accuracy of elasticity calculations. However, depending on the elastic properties (Young's modulus) of the imaging object, the parameter T must be set differently. Because a larger Young's modulus increases the shear wave velocity, the parameter T should be increased, which is not conducive to imaging objects with large differences in Young's modulus.

[0009] Analysis revealed that existing morphological distortion correction techniques are only applicable to imaging objects with regular surface morphology. However, endoscopic objects, such as blood vessels, the digestive tract, and the reproductive tract, lack the characteristic layers of the retina and cornea that remain constant, making them difficult to fit using polynomials. Furthermore, existing deformation deviation correction techniques only apply a delay time interval parameter to imaging objects with specific elastic properties. Objects with significantly different elastic properties require adjusting the delay time interval, resulting in a lack of adaptability. Summary of the Invention

[0010] The purpose of the present invention is to overcome the above-mentioned shortcomings of the prior art and provide a method for suppressing motion artifacts in endoscopic optical coherence elasticity images. The method comprises the following steps:

[0011] Obtain intensity images and phase difference images corresponding to the target OCT spectral signal;

[0012] For the intensity image, correcting morphological distortion based on the frequency of motion disturbances;

[0013] For the phase difference image, the moment when the excitation causes deformation in the imaging object is detected, and the displacement caused by the motion is subtracted from the detected displacement, and the displacement caused by the excitation is retained to correct the deformation deviation;

[0014] The optical coherence elastography image is reconstructed based on the morphological distortion correction results and the deformation deviation correction results.

[0015] Compared to existing technologies, the present invention offers the advantage of a motion artifact suppression method for endoscopic optical coherence elastography. The method extracts the surface of the endoscopic imaging object (vascular, digestive, reproductive, and other luminal structures) and corrects morphological distortion based on the frequency of motion interference. Furthermore, the method detects the moment when an excitation causes deformation in the imaging object and corrects for deformation deviation by subtracting the displacement caused by motion from the displacement caused by the excitation. In summary, the present invention can simultaneously correct for both elasticity deviations in endoscopic optical coherence elastography images and morphological distortions of the imaging object caused by physiological motion.

[0016] Further features and advantages of the present invention will become apparent from the following detailed description of exemplary embodiments of the present invention with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and, together with the description, serve to explain the principles of the invention.

[0018] Figure 1 Schematic diagram of a normal OCT three-dimensional image and an image affected by motion artifacts in the prior art;

[0019] Figure 2 It is a schematic diagram of the deformation process in the prior art;

[0020] Figure 3 This is a schematic diagram of identifying feature layers and performing spatial polynomial fitting in the prior art;

[0021] Figure 4 It is a schematic diagram of calculating Doppler phase difference image in the prior art;

[0022] Figure 5 is a flow chart of a method for suppressing motion artifacts in endoscopic optical coherence elasticity images according to one embodiment of the present invention;

[0023] Figure 6 1 is a schematic diagram of a process of a method for suppressing motion artifacts in endoscopic optical coherence elasticity images according to an embodiment of the present invention;

[0024] Figure 7 is a schematic diagram of morphological distortion correction according to one embodiment of the present invention;

[0025] Figure 8 is a schematic diagram of the relationship between the phase difference image and the intensity image, as well as the velocity curve and the displacement curve according to one embodiment of the present invention;

[0026] Figure 9 2 is a schematic diagram of deformation deviation correction according to an embodiment of the present invention. DETAILED DESCRIPTION

[0027] Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that unless otherwise specifically stated, the relative arrangement of components and steps, numerical expressions and numerical values ​​set forth in these embodiments do not limit the scope of the present invention.

[0028] The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.

[0029] Technologies, methods, and equipment known to ordinary technicians in the relevant art may not be discussed in detail, but where appropriate, the technologies, methods, and equipment should be considered part of the specification.

[0030] In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not limiting. Therefore, other examples of the exemplary embodiments may have different values.

[0031] It should be noted that like reference numerals and letters refer to like items in the following figures, and therefore, once an item is defined in one figure, it need not be further discussed in subsequent figures.

[0032] This paper proposes a method for suppressing motion artifacts in endoscopic optical coherence elasticity images. The method generally involves extracting surface features of image portions with morphological distortion using image segmentation and morphological operations. A low-pass filter is then constructed based on the frequency components of the motion. The extracted curve is processed, and the image is corrected using the filtered curve as a reference. For portions of the image with deformation deviation, a window of appropriate size is first selected to calculate the displacement caused by motion. The deformation deviation is then corrected by subtracting the displacement caused by motion from the displacement caused by the excitation.

[0033] Combine Figure 5 and Figure 6 As shown, the provided method for suppressing motion artifacts in endoscopic optical coherence elasticity images comprises the following steps:

[0034] Step S110 : correcting the morphological distortion of the target image based on the frequency of motion interference.

[0035] Specifically, after collecting the OCT spectral signal, the raw data is Fourier transformed to extract the amplitude information of the signal, and the signals at different positions are processed to form an intensity image. In addition, the signal-to-noise ratio of the intensity image can be improved. For example, the signal-to-noise ratio of the intensity image can be improved by taking the average value of multiple frames of intensity images at the same position obtained by M-mode imaging to obtain a clearer intensity image. Next, the intensity image is binarized and segmented. For example, the Otsu threshold segmentation method or other image segmentation methods are used to separate the target object (biological tissue) and the background. Finally, the morphological opening and closing operations are applied to the binary image in sequence to make the area where the target object is located a continuous, hole-free area. The processed binary image is called a target mask.

[0036] In one embodiment, a method for correcting morphological distortion includes extracting and smoothing the upper surface of the target object. First, on each column of the target mask, points with the minimum row number and a true value are selected. These points form a curve, namely the target curve. The target curve represents the upper surface of the target object and is affected by physiological motion and presents a fluctuating state. Figure 7 The schematic diagram of morphological distortion correction is shown in Figure 7(a) is the OCT image of the target object with morphological distortion, the green curve is the target curve, Figure 7 (b) is a schematic diagram of the target curve and the smoothed curve on the target object surface. Figure 7 (c) is the corrected OCT image. Next, a Fourier transform is performed on the target curve. The cutoff frequency of the low-pass filter is determined based on the lowest-frequency motion component in the spectrum. This low-pass filter is then constructed to smooth the target curve, resulting in a smoothed target curve. The difference between the smoothed curve and the target curve is then used to calculate the row shift for each column of the image. This shift is then applied to all columns of the (distortion-corrected) OCT image, ultimately yielding an image corrected for morphological distortion.

[0037] In step S120 , for the target image, the moment when the excitation causes deformation in the imaging object is detected, and the displacement caused by the motion is subtracted from the detected displacement, and the displacement caused by the excitation is retained to correct the deformation deviation.

[0038] To reconstruct the OCE image, first calculate the phase difference image. Use the phase difference at different times at the same position obtained by M-mode imaging to calculate the phase difference. For example, the Kasai autocorrelation algorithm can be used to calculate the phase difference. Calculate the phase difference at different positions to form a phase difference image. Figure 8 As shown, Figure 8 (a) is a schematic diagram of the relationship between the phase difference image and the intensity image, where x is the column number, indicating the lateral position, and z is the row number, indicating different depth positions. Figure 8 (b) is a schematic diagram of the velocity curve and displacement curve.

[0039] Combine Figure 8 As shown in (a), the target mask is applied to the phase difference image, that is, the target mask is multiplied by the corresponding points in the phase difference image to select the area where the target object is located, eliminating unnecessary calculations on the background. In each unit of the image, the speed is calculated from the phase difference, expressed as:

[0040]

[0041] Among them, the subscript x is the column number of the unit, the subscript z is the row number of the unit, and v z,x is the axial motion speed of the unit, is the phase difference, λ is the central wavelength of the light source, n is the refractive index of the sample, τ is the data acquisition time interval, and θ is the Doppler angle. The velocities at different times are arranged in sequence to form a velocity curve. The displacement at each time is calculated by accumulating the velocity over time, and the displacements at different times are arranged in sequence to form a displacement curve. Figure 8 The deformation of each unit shown in (b) is the maximum value of the displacement curve. The deformation of each unit is calculated to form an OCE image.

[0042] In one embodiment, the method for correcting the deformation deviation is to deduct the displacement caused by motion disturbance and only retain the displacement caused by excitation. Figure 9 is a schematic diagram of deformation deviation correction, Figure 9 (a) is the velocity curve and displacement curve before correction. The blue arrow indicates the velocity mutation point, and the green dotted box indicates the time window of motion interference velocity calculation. Figure 9 The red curve in (a) is the detected displacement curve, which includes the displacement caused by excitation and the displacement caused by motion. Figure 9 (b) is the corrected velocity curve and displacement curve. The corrected displacement curve only contains the displacement caused by excitation.

[0043] Specifically, first, find the velocity mutation point caused by the excitation, such as Figure 9 As shown by the blue arrow in (a), for example, the Cumulative Sum Control Chart (CUSUM) method can be used to detect the velocity mutation point. The moment corresponding to the velocity mutation point is the excitation start moment. Then, the time window of the motion interference velocity is determined in the velocity curve. The velocity change caused by the elastic excitation should not exist within this time window. The time window can be selected before the elastic excitation starts or after the target object recovers its deformation (e.g., Figure 9 Assume that the motion interference velocity is uniform within the time of one M-mode imaging, and calculate the average velocity within the time window as the velocity correction. Then, subtract the velocity correction from the original velocity curve to obtain the corrected velocity curve, and recalculate the displacement curve. The corrected velocity curve and displacement curve are shown in Figure 2. Figure 9 (b) To extract the displacement caused by excitation, the displacement of the displacement curve at the time of excitation is considered the displacement baseline, as the velocity mutation point corresponds to the excitation start time. The deformation of each element is the maximum value of the displacement curve minus the displacement baseline.

[0044] Step S130 : translating the OCE image according to the morphological distortion correction result and the deformation deviation correction result to obtain a corrected OCE image.

[0045] After correcting the morphological distortion and deformation deviation in the image, the correction results can be used to obtain a reconstructed OCE image. The reconstructed OCE image can effectively suppress motion artifacts in the image, improving image quality and accuracy.

[0046] In summary, compared with the prior art, the present invention has the following advantages:

[0047] 1) The present invention proposes for the first time a solution that can simultaneously correct the morphological distortion and deformation deviation of OCE images, and it has been verified that the correction effect is good and has a wide range of adaptability.

[0048] 2) In the process of correcting morphological distortion, the present invention extracts the upper surface signal of the target object to form a curve, and performs low-pass filtering on the curve according to the frequency of motion interference for smoothing. This design is more suitable for endoscopic scenarios with irregular surface morphology, lack of feature layers, and large differences in elastic properties, and thus has better adaptability and good robustness.

[0049] 3) During the deformation deviation correction process, the present invention identifies the moment when the imaging object begins to deform due to the excitation (the velocity mutation point). A time window is set during the period without the excitation to calculate the velocity of the motion disturbance. The displacement caused by the motion disturbance is deducted, leaving only the displacement caused by the excitation. This method of determining the filtering parameters and correction amount based on the frequency and velocity of the motion disturbance further improves adaptability.

[0050] The present invention may be a system, a method and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for causing a processor to implement various aspects of the present invention.

[0051] Computer-readable storage medium can be a tangible device that can keep and store the instructions used by the instruction execution device.Computer-readable storage medium can be, for example, but not limited to, an electrical storage device, a magnetic storage device, an optical storage device, an electromagnetic storage device, a semiconductor storage device or any suitable combination thereof.More specific examples (non-exhaustive list) of computer-readable storage medium include: a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), a static random access memory (SRAM), a portable compact disc read-only memory (CD-ROM), a digital versatile disk (DVD), a memory stick, a floppy disk, a mechanical encoding device, for example, a punch card or a convex structure in a groove having instructions stored thereon, and any suitable combination thereof.Computer-readable storage medium used herein is not interpreted as a transient signal itself, such as radio waves or other freely propagating electromagnetic waves, electromagnetic waves propagated by waveguides or other transmission media (for example, light pulses by fiber optic cables), or electrical signals transmitted by wires.

[0052] The computer-readable program instructions described herein can be downloaded from a computer-readable storage medium to each computing / processing device, or downloaded to an external computer or external storage device via a network, such as the Internet, a local area network, a wide area network, and / or a wireless network. The network can include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. The network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards the computer-readable program instructions to be stored in the computer-readable storage medium in each computing / processing device.

[0053] The computer program instructions for performing the operation of the present invention can be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, Python, and conventional procedural programming languages ​​such as "C" language or similar programming languages. The computer readable program instructions can be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer, partially on a remote computer, or completely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (e.g., using an Internet service provider to connect via the Internet). In some embodiments, an electronic circuit, such as a programmable logic circuit, a field programmable gate array (FPGA), or a programmable logic array (PLA), is personalized by utilizing the state information of the computer readable program instructions, and the electronic circuit can execute the computer readable program instructions, thereby realizing various aspects of the present invention.

[0054] Various aspects of the present invention are described herein with reference to flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the present invention. It should be understood that each block of the flowcharts and / or block diagrams, and combinations of blocks in the flowcharts and / or block diagrams, can be implemented by computer-readable program instructions.

[0055] These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine, so that when these instructions are executed by the processor of the computer or other programmable data processing device, a device is generated that implements the functions / actions specified in one or more blocks in the flowchart and / or block diagram. These computer-readable program instructions can also be stored in a computer-readable storage medium, where these instructions cause the computer, programmable data processing device, and / or other device to operate in a specific manner. Thus, the computer-readable medium storing the instructions comprises an article of manufacture that includes instructions for implementing various aspects of the functions / actions specified in one or more blocks in the flowchart and / or block diagram.

[0056] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device so that a series of operational steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the instructions executed on the computer, other programmable data processing apparatus, or other device to implement the functions / actions specified in one or more blocks in the flowchart and / or block diagram.

[0057] The flowcharts and block diagrams in the accompanying drawings show the possible implementation architecture, functions and operations of the systems, methods and computer program products according to multiple embodiments of the present invention. In this regard, each box in the flowchart or block diagram can represent a module, program segment or part of an instruction, and the module, program segment or part of the instruction contains one or more executable instructions for implementing the specified logical function. In some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified function or action, or can be implemented by a combination of dedicated hardware and computer instructions. It is well known to those skilled in the art that implementation by hardware, implementation by software, and implementation by a combination of software and hardware are all equivalent.

[0058] While various embodiments of the present invention have been described above, the foregoing description is intended to be illustrative, non-exhaustive, and not limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments. The terminology used herein is selected to best explain the principles of the embodiments, their practical applications, or technological improvements in the marketplace, or to enable others skilled in the art to understand the embodiments disclosed herein. The scope of the present invention is defined by the appended claims.

Claims

1. A method for suppressing motion artifacts in endoscopic optical coherence elasticity images, comprising the following steps: Obtain intensity images and phase difference images corresponding to the target OCT spectral signal; For the intensity image, correcting morphological distortion based on the frequency of motion disturbances; For the phase difference image, detecting the moment when the excitation causes deformation in the imaging object, and subtracting the displacement caused by the motion from the detected displacement, retaining the displacement caused by the excitation to correct the deformation deviation; The optical coherence elastography image is reconstructed based on the morphological distortion correction results and the deformation deviation correction results.

2. The method according to claim 1, characterized in that For the intensity image, correcting morphological distortion based on the frequency of motion disturbances includes: improving the signal-to-noise ratio of the intensity image to obtain an enhanced intensity image; performing binary segmentation on the enhanced intensity image to segment the target object and the background to obtain a binary image; Applying morphological opening and closing operations to the binary image in sequence to make the region where the target object is located a continuous region without holes, thereby obtaining a target mask; extracting a target curve from the target mask, where the target curve represents an upper surface of the target object; Performing Fourier transform on the target curve, determining the cutoff frequency of a low-pass filter according to the lowest-frequency motion component in the spectrum, and smoothing the target curve using the low-pass filter to obtain a smooth target curve; The row translation amount of each column of the image is calculated using the difference between the smoothed target curve and the target curve, and all columns of the optical coherence elastography image are translated to obtain an image after morphological distortion correction.

3. The method according to claim 2, characterized in that For the phase difference image, detecting the moment when the excitation causes deformation in the imaging object, and correcting the deformation deviation by subtracting the displacement caused by the motion from the displacement caused by the excitation includes: Multiplying the target mask with the corresponding points of the phase difference image to select the area where the target object is located; For the intensity image and the phase difference image, a velocity curve is obtained by utilizing the relationship between phase difference and velocity; Determine a speed correction amount, and subtract the speed correction amount from the speed curve to obtain a corrected speed curve and displacement curve; For the corrected displacement curve, the displacement caused by motion interference is deducted, and the displacement caused by excitation is retained as the target to determine the deformation deviation.

4. The method according to claim 2, characterized in that The signal-to-noise ratio of the intensity image is improved by taking the average value of multiple frames of intensity images at the same position obtained by M-mode imaging.

5. The method according to claim 2, characterized in that The target mask The steps include: Use Otsu threshold segmentation method to separate the target object and background to obtain a preliminary binary image; Morphological opening and closing operations are sequentially applied to the preliminary binary image to make the region where the target object is located become a continuous region without holes, and the processed binary image is used as the target mask.

6. The method according to claim 1, characterized in that The phase difference image is obtained according to the following steps: For the same position at different times obtained by M-mode imaging, the phase difference is calculated using the Cathay autocorrelation algorithm; The phase difference at different positions is calculated to form the phase difference image.

7. The method according to claim 3, characterized in that The deformation deviation is determined according to the following steps: Find the velocity mutation point caused by the excitation, and take the time corresponding to the velocity mutation point as the excitation starting time; Determining a time window of motion disturbance velocity in the velocity curve, wherein the time window does not include velocity changes caused by elastic excitation; Calculating the average speed within the time window as the speed correction; Subtracting the speed correction amount from the original speed curve to obtain a corrected speed curve, and recalculating the displacement curve; The displacement corresponding to the recalculated displacement curve at the start of excitation is used as the displacement baseline, and the deformation of each image unit is the maximum value of the recalculated displacement curve minus the displacement baseline to determine the deformation deviation.

8. The method according to claim 1, characterized in that The intensity image is obtained according to the following steps: after collecting the OCT spectrum signal, the original data is Fourier transformed to extract the amplitude information of the signal, and the signals at different positions are processed to form an intensity image.

9. A computer-readable storage medium having a computer program stored thereon, wherein: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

10. A computer device comprising a memory and a processor, wherein a computer program capable of being run on the processor is stored in the memory, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

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